Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/807#discussion_r13838530
--- Diff:
external/flume/src/main/scala/org/apache/spark/streaming/flume/FlumePollingInputDStream.scala
---
@@ -0,0 +1,189 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.streaming.flume
+
+
+import java.io.{ObjectOutput, ObjectInput, Externalizable}
+import java.net.InetSocketAddress
+import java.nio.ByteBuffer
+import java.util.concurrent.{TimeUnit, Executors}
+
+import scala.collection.JavaConversions._
+import scala.reflect.ClassTag
+
+import com.google.common.util.concurrent.ThreadFactoryBuilder
+import org.apache.avro.ipc.NettyTransceiver
+import org.apache.avro.ipc.specific.SpecificRequestor
+import org.jboss.netty.channel.socket.nio.NioClientSocketChannelFactory
+
+import org.apache.spark.Logging
+import org.apache.spark.flume.{SparkSinkEvent, SparkFlumeProtocol}
+import org.apache.spark.storage.StorageLevel
+import org.apache.spark.streaming.StreamingContext
+import org.apache.spark.streaming.dstream.ReceiverInputDStream
+import org.apache.spark.streaming.receiver.Receiver
+
+/**
+ * A [[ReceiverInputDStream]] that can be used to read data from several
Flume agents running
+ * [[org.apache.spark.flume.sink.SparkSink]]s.
+ * @param ssc_ Streaming context that will execute this input stream
+ * @param addresses List of addresses at which SparkSinks are listening
+ * @param maxBatchSize Maximum size of a batch
+ * @param parallelism Number of parallel connections to open
+ * @param storageLevel The storage level to use.
+ * @tparam T Class type of the object of this stream
+ */
+class FlumePollingInputDStream[T: ClassTag](
+ @transient ssc_ : StreamingContext,
+ val addresses: Seq[InetSocketAddress],
+ val maxBatchSize: Int,
+ val parallelism: Int,
+ storageLevel: StorageLevel
+) extends ReceiverInputDStream[SparkFlumePollingEvent](ssc_) {
+ /**
+ * Gets the receiver object that will be sent to the worker nodes
+ * to receive data. This method needs to defined by any specific
implementation
+ * of a NetworkInputDStream.
+ */
+ override def getReceiver(): Receiver[SparkFlumePollingEvent] = {
+ new FlumePollingReceiver(addresses, maxBatchSize, parallelism,
storageLevel)
+ }
+}
+
+private[streaming] class FlumePollingReceiver(
+ addresses: Seq[InetSocketAddress],
+ maxBatchSize: Int,
+ parallelism: Int,
+ storageLevel: StorageLevel
+) extends Receiver[SparkFlumePollingEvent](storageLevel) with Logging {
+
+ lazy val channelFactoryExecutor =
+ Executors.newCachedThreadPool(new
ThreadFactoryBuilder().setDaemon(true).
+ setNameFormat("Flume Receiver Channel Thread - %d").build())
+
+ lazy val channelFactory =
+ new NioClientSocketChannelFactory(channelFactoryExecutor,
channelFactoryExecutor)
+
+ lazy val receiverExecutor = Executors.newFixedThreadPool(parallelism,
+ new ThreadFactoryBuilder().setDaemon(true).setNameFormat("Flume
Receiver Thread - %d").build())
+
+ private var connections = Array.empty[FlumeConnection] // temporarily
empty, filled in later
+
+ override def onStart(): Unit = {
+ // Create the connections to each Flume agent.
+ connections = addresses.map(host => {
+ val transceiver = new NettyTransceiver(host, channelFactory)
+ val client =
SpecificRequestor.getClient(classOf[SparkFlumeProtocol.Callback], transceiver)
+ new FlumeConnection(transceiver, client)
+ }).toArray
+
+ // Threads that pull data from Flume.
+ val dataReceiver = new Runnable {
+ override def run(): Unit = {
+ var counter = 0
+ while (true) {
+ counter = counter % connections.size
+ val client = connections(counter).client
+ counter += 1
+ val batch = client.getEventBatch(maxBatchSize)
+ val seq = batch.getSequenceNumber
+ val events: java.util.List[SparkSinkEvent] = batch.getEvents
+ logDebug("Received batch of " + events.size() + " events with
sequence number: " + seq)
+ try {
+ // Convert each Flume event to a serializable SparkPollingEvent
+ events.foreach(event => {
+ store(SparkFlumePollingEvent.fromSparkSinkEvent(event))
+ })
+ // Send an ack to Flume so that Flume discards the events from
its channels.
+ client.ack(seq)
+ } catch {
+ case e: Throwable =>
+ try {
--- End diff --
same here, catch only exceptions.
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